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We're here to help you find itIntroduction to MATLAB for Data Science Course Overview
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Flexi Video | 16,449 |
Official E-coursebook | |
Exam Voucher (optional) | |
Hands-On-Labs2 | 4,159 |
+ GST 18% | 4,259 |
Total Fees (without exam & Labs) |
22,359 (INR) |
Total Fees (with Labs) |
28,359 (INR) |
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Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
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Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.
Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.
Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.
Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.
Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.
Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
For Introduction to MATLAB for Data Science training, the course prerequisites are typically as follows:
1. Basic programming knowledge: Familiarity with programming concepts such as variables, loops, conditionals, and functions in any programming language.
2. Fundamental understanding of linear algebra: Concepts like matrices, vectors, matrix manipulations, and basic linear algebra operations are essential.
3. Basic calculus and statistics: A working knowledge of concepts like differentiation, integration, mean, standard deviation, and probability can be helpful.
4. Familiarity with data file formats: Understanding of CSV, Excel, or other text-based data file formats is useful for importing and exporting data.
5. Understanding of data analysis and visualization concepts: Basic concepts around data analysis and using charts, graphs, and other visualization techniques for interpreting data results.
6. MATLAB installation: Having MATLAB software installed on your system, including necessary toolboxes related to data science like the Statistics and Machine Learning Toolbox.
Remember that the prerequisites may vary slightly depending on the specific course or university offering the training. It's always a good idea to check with the course provider for any additional prerequisites or requirements.
Introduction to MATLAB for Data Science certification training provides a comprehensive understanding of the MATLAB programming language, which is crucial in data analysis and visualization. This course covers general topics like basics of MATLAB, importing and exporting data, data analysis, statistical operations, and creating visualizations. Students will gain hands-on experience with MATLAB, enabling them to apply their learning to real-world data science scenarios, thereby enhancing their skills and increasing their employability in the field.
Introduction to MATLAB for Data Science equips learners with powerful tools for statistical analysis and visualization. Gaining proficiency in this course enables individuals to efficiently analyze complex data, streamline processes, and develop robust predictive models, giving them a competitive edge in a data-driven world.
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Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.
Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.
Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.
Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.
Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.
Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs